Abstract: We present promising results for real-time vehicle visual detection, obtained
with adaBoost using new original ?keypoints presence features?. These
weak-classifiers produce a boolean response based on presence or absence in the
tested image of a ?keypoint? (~ a SURF interest point) with a descriptor
sufficiently similar (i.e. within a given distance) to a reference descriptor
characterizing the feature. A first experiment was conducted on a public image
dataset containing lateral-viewed cars, yielding 95% recall with 95% precision
on test set. Moreover, analysis of the positions of adaBoost-selected keypoints
show that they correspond to a specific part of the object category (such as
?wheel? or ?side skirt?) and thus have a ?semantic? meaning.